Image noise reduction based on block matching in wavelet frame domain

This paper describes the shear wavelet frame transform (SWFT) with two sets of block matching for the application of image denoising. Using the SWFT, we can analyze anisotropic features, such as edges in images. To assign the directionality we use a shear matrix for the continuous wavelet transform....

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Bibliographic Details
Published inMultimedia tools and applications Vol. 79; no. 35-36; pp. 26327 - 26344
Main Authors Muhammad, Nazeer, Bibi, Nargis, Kamran, Muhammad, Bashir, Yasir, Park, Sangwoong, Kim, Dai-Gyoung
Format Journal Article
LanguageEnglish
Published New York Springer US 01.09.2020
Springer Nature B.V
Subjects
Algorithms
Computer Communication Networks
Computer Science
Continuous wavelet transform
Data Structures and Information Theory
Matching
Multimedia Information Systems
Noise reduction
Signal to noise ratio
Special Purpose and Application-Based Systems
Wavelet transforms
Minimum mean square error
Block mathcing
Edge enhancing
Shear wavelet frames
Image denoising
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Summary:This paper describes the shear wavelet frame transform (SWFT) with two sets of block matching for the application of image denoising. Using the SWFT, we can analyze anisotropic features, such as edges in images. To assign the directionality we use a shear matrix for the continuous wavelet transform. Block matching with 3-D collaborative filtering has been incorporated for hard thresholding of reference block. We deploy two sets of the search neighborhood blocks to avoid the artifacts while removing heavy noise. The proposed algorithm is evaluated on standard benchmark images and outperforms the recent state-of-the-art methods in terms of peak signal to noise ratio.
ISSN:1380-7501
1573-7721
DOI:10.1007/s11042-020-09158-0